Consumer response to functional foods produced by conventional, organic, or genetic manipulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The agro‐food industry is developing a “second generation” of genetically modified (GM) foods that can offer functional health benefits to consumers. Many consumers, however, are turning to organic foods in order to avoid GM foods. This report attempts to differentiate consumer valuation of functional health properties in conventional, organic, and GM foods. A representative sample of 1,008 Canadian household food shoppers responded to twelve stated‐choice experiments during a telephone survey. Because opinions about organic and GM foods varied greatly, random parameters logit models were used to analyze their choices. Results indicate that many Canadian consumers will avoid GM foods, regardless of the presence of functional health properties. For others, the introduction of GM functional plant foods should increase acceptance of GM production methods, but many consumers will likely avoid functional foods derived from GM animals. The organic food industry could also profit from the introduction of organic functional foods. [EconLit citations: I120; D120.] © 2004 Wiley Periodicals, Inc. Agribusiness 20: 155–166, 2004.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it